Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
504570 | Computerized Medical Imaging and Graphics | 2010 | 8 Pages |
Abstract
This paper presents an approach for breast cancer diagnosis in digital mammogram using curvelet transform. After decomposing the mammogram images in curvelet basis, a special set of the biggest coefficients is extracted as feature vector. The Euclidean distance is then used to construct a supervised classifier. The experimental results gave a 98.59% classification accuracy rate, which indicate that curvelet transformation is a promising tool for analysis and classification of digital mammograms.
Keywords
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Science Applications
Authors
Mohamed Meselhy Eltoukhy, Ibrahima Faye, Brahim Belhaouari Samir,